# SET INPUT AND OUTPUT PATH
# Using function here() wil provide path to the OCR_Pipeline(package) folder on your computer,
# the input and output separate folers are in "/OCR_Pipeline/Data". 
# Recomend to move the result to different folder before every analysis.
#
# To choose different folder in your coputer as I/O folder write entire Path to the folder. 
INPUT_PATH  <- here('/Data/INPUT')
OUTPUT_PATH <- here('/Data/OUTPUT')

OCR

Identyfy Outliars

Removed outliars in each iteration:

## 1  Well outliares:  798 -- 10.37037 % 
## 2  Well outliares:  161 -- 2.092268 % 
## 3  Well outliares:  71 -- 0.9226771 % 
## 4  Well outliares:  9 -- 0.1169591 % 
## 5  Well outliares:  0 -- 0 % 
## 1  Point outliares:  229 -- 3.538866 % 
## 2  Point outliares:  79 -- 1.220831 % 
## 3  Point outliares:  27 -- 0.4172462 % 
## 4  Point outliares:  12 -- 0.1854427 % 
## 5  Point outliares:  7 -- 0.1081749 % 
## 6  Point outliares:  3 -- 0.04636069 % 
## 7  Point outliares:  1 -- 0.01545356 % 
## 8  Point outliares:  0 -- 0 % 
## Tolat well outliars:  13.83489 % 
## Tolat single point outliars:  4.766977 %

Procentage of all outliars across samples

TO DO: convert graph to aditive add legends

Interval estimates

Int1 Int2 Int3 Int4 Int5 Sample
4.096 3.136 4.959 2.870 3.159 24-post-0
2.913 1.739 3.425 1.641 1.770 24-pre-1
4.078 3.088 5.162 2.962 3.119 31 post-2
4.824 3.900 6.185 3.633 3.869 42 pre-2
3.493 2.512 4.417 2.274 2.407 33-pre-3
3.939 2.891 4.741 2.869 2.916 34-post-4
3.376 2.460 3.982 2.051 2.412 34-pre-5
3.696 2.920 4.638 2.745 2.794 S-36pre-6
3.633 2.803 4.509 2.663 2.688 S-43pre-6
3.605 2.682 4.400 2.481 2.591 36-pre-7
3.592 2.481 4.677 2.393 2.563 39-post-8
3.586 2.409 4.564 2.428 2.571 39-pre-9
3.000 1.586 3.949 1.559 1.925 42 post-10
3.447 2.529 3.911 1.872 3.022 #46 pre-10
3.839 2.893 4.616 2.800 2.895 43 post-11
3.761 2.937 4.051 2.782 3.565 49 pre-11
3.981 2.972 4.886 2.708 2.960 46 post-12
3.792 2.753 4.792 2.339 2.899 40 pre-12
3.555 2.763 4.378 2.942 2.929 49-post-13

Error of esstimates

Int1 Int2 Int3 Int4 Int5 Sample
0.012 0.016 0.020 0.015 0.028 24-post-0
0.018 0.024 0.029 0.023 0.031 24-pre-1
0.009 0.011 0.015 0.011 0.016 31 post-2
0.011 0.014 0.019 0.014 0.018 42 pre-2
0.016 0.022 0.027 0.020 0.029 33-pre-3
0.016 0.021 0.027 0.020 0.029 34-post-4
0.041 0.053 0.068 0.052 0.066 34-pre-5
0.017 0.022 0.026 0.020 0.032 S-36pre-6
0.025 0.031 0.053 0.030 0.041 S-43pre-6
0.014 0.017 0.022 0.017 0.024 36-pre-7
0.029 0.034 0.041 0.035 0.045 39-post-8
0.016 0.020 0.028 0.020 0.028 39-pre-9
0.044 0.061 0.073 0.063 0.090 42 post-10
0.067 0.079 0.105 0.087 0.108 #46 pre-10
0.014 0.018 0.024 0.017 0.024 43 post-11
0.027 0.039 0.043 0.036 0.044 49 pre-11
0.023 0.028 0.033 0.027 0.035 46 post-12
0.023 0.027 0.036 0.027 0.036 40 pre-12
0.016 0.022 0.026 0.019 0.033 49-post-13

Bioenergetics

## Using Sample as id variables

ECAR